Name
Abstract | ||
|---|---|---|
A new adaptive pole placement controller for nonlinear systems using a modified neural network is presented. The modified neural network is composed of two parts: one is a linear neural network (LNN), and the other is a multilayer feedforward neural network C:MFNN). Then a fast learning algorithm is proposed for training the network. The adaptive control design is based on the LNN and MFNN. Simulation results reveal that the new adaptive pole placement controller can effectively control a class of nonlinear systems. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1016/S1474-6670(17)43401-X | IFAC Proceedings Volumes |
Keywords | Field | DocType |
pole placement,adaptive control,nonlinear systems,neural networks,learning algorithm | Control theory,Feedforward neural network,Control theory,Full state feedback,Probabilistic neural network,Time delay neural network,Adaptive control,Backpropagation,Artificial neural network,Mathematics | Journal |
Volume | Issue | ISSN |
30 | 6 | 1474-6670 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fuli Wang | 1 | 52 | 12.61 |
| Mingzhong Li | 2 | 20 | 4.58 |
| Yinghuai Yang | 3 | 0 | 0.34 |